DESCRIPTION: In order to gain a better understanding of the phenomenon of small area variations and the reasons for it, the primary objective of this study is to examine empirically the relationship between the average severity of hospitalized patients and small area hospitalization rates. We will use data on utilization in 2000 by Massachusetts Medicare patients for 20 medical conditions. The study will test the hypotheses that 1) patient severity is negatively related to "practice style," i.e., in small areas with higher hospitalization rates, physicians admit patients with a lower average severity of illness; and 2) patient severity is not related to the amount of disease identified in the population. Previous studies of small area variations in hospitalization rates rarely have included any measure of severity of patient illness despite the strong theoretical basis for severity to be a major driver of hospitalization rates. Moreover, previous studies have only used data on hospitalizations. Thus, it has not been possible to distinguish the extent to which differences in hospitalization rates are due to: 1) differences in the likelihood that patients diagnosed with a disease are admitted to a hospital, i.e., differences in "practice style," versus 2) differences in the amount of disease diagnosed in different areas, which we refer to as differences in the amount of "identified disease" or the "disease effect." In this study we will use data on both inpatient and outpatient visits in order to distinguish amount of "practice style" variation from that of "identified disease" in explaining variations in hospitalization rates. We focus on medical conditions because of greater uncertainty regarding the need for hospital care (rather than care in an alternative setting) compared to surgical conditions. We will use the APR-DRG patient severity classification system to measure severity of patients admitted to hospital. For each selected DRG, the relationship between severity and practice style, and that between severity and identified disease will be investigated using correlation analysis and adjusting for random variation using extensions of the model that underlies McPherson's "systematic component of variation." We will also collect data for a set of socioeconomic and supply factors and use multivariate analysis to help determine the extent to which: 1) socioeconomic (community) and supply (health services system) factors modify the relationship between practice style and severity; and 2) socioeconomic and supply factors explain variations in the disease effect. Our underlying hypothesis is that the socioeconomic and supply factors will have a relatively weak relationship to practice style their relationship with the disease effect.